BACKGROUND:Rapid and accurate segmentation of brain tissue in medical images is of great significance for three-dimensional biomechanical modeling and diagnosis of craniocerebral injuries.Currently,artificial intelligence(AI)-based baseline models exhibit excellent generalization capabilities on large-scale datasets.However,due to the specificity and complexity of craniocerebral tissues,these models have certain limitations in their application to craniocerebral tissue segmentation.Additionally,the scarcity of craniocerebral tissue samples makes it difficult for baseline models to achieve precise segmentation results through fine-tuning.OBJECTIVE:To construct a craniocerebral tissue segmentation model based on texture feature retrieval enhancement to improve segmentation accuracy under a small number of samples.METHODS:Segment Anything in Medical Images(MedSAM)model was selected as the basic framework,and texture features were combined with deep learning to build a brain tissue segmentation model based on texture feature retrieval enhancement(DP-MedSAM).Dice Coefficient and mean intersection over union(MIoU)were selected to evaluate the efficiency of image segmentation results.In comparison with the original MedSAM model,the ablation experiment systematically evaluated the influence of key components on the model performance.The sensitivities of MedSAM,the Segment Anything Model(SAM)for medical image segmentation(SAM-Med2D)and DP-MedSAM in the mandible,left optic nerve,and left parotid gland were compared.RESULTS AND CONCLUSION:(1)By verifying the impact of the number of point prompts on segmentation results on the HaN-Seg dataset,the experimental results indicated that the optimal Dice score was achieved with the addition of three points.(2)DP-MedSAM demonstrated performance improvements compared with MedSAM and SAM-Med2D on two datasets(HaN and Public Domain Database for Computational Anatomy).Especially on the Public Domain Database for Computational Anatomy dataset,in terms of the MIoU metric,DP-MedSAM outperformed MedSAM by 6.59％and SAM-Med2D by 37.35％;in terms of the Dice metric,DP-MedSAM outperformed MedSAM and SAM-Med2D by 4.34％and 25.32％,respectively.(3)The ablation experiment results showed that removing the texture feature extraction module in the DP-MedSAM model,relying solely on original image features,led to a significant decrease in results on the test set.Furthermore,removing the vector cache database and its retrieval enhancement function from the model,which deprived the ability of the model to perform similarity retrieval using an external knowledge base,further reduced model performance.(4)Under conditions of limited data resources,the DP-MedSAM model outperformed the other two models in all evaluation metrics.The DP-MedSAM model performed excellently when processing simple and moderately difficult samples,demonstrating a clear advantage over the other two models and indicating good generalization ability.Processing the fine structures of difficult samples placed higher demands on the model's segmentation capabilities.Although the performance of the DP-MedSAM model declined slightly,it still outperformed the other two models.(5)This study proposes an innovative craniocerebral tissue segmentation model,DP-MedSAM,which improves the baseline model's performance in capturing local details and global structural information in medical images by introducing target region texture feature extraction.Through vector similarity retrieval technology,DP-MedSAM can retrieve the feature vector most similar to the current target region from a pre-constructed vector database,providing more precise guiding information for the segmentation process.

BACKGROUND:Rapid and accurate segmentation of brain tissue in medical images is of great significance for three-dimensional biomechanical modeling and diagnosis of craniocerebral injuries.Currently,artificial intelligence(AI)-based baseline models exhibit excellent generalization capabilities on large-scale datasets.However,due to the specificity and complexity of craniocerebral tissues,these models have certain limitations in their application to craniocerebral tissue segmentation.Additionally,the scarcity of craniocerebral tissue samples makes it difficult for baseline models to achieve precise segmentation results through fine-tuning.OBJECTIVE:To construct a craniocerebral tissue segmentation model based on texture feature retrieval enhancement to improve segmentation accuracy under a small number of samples.METHODS:Segment Anything in Medical Images(MedSAM)model was selected as the basic framework,and texture features were combined with deep learning to build a brain tissue segmentation model based on texture feature retrieval enhancement(DP-MedSAM).Dice Coefficient and mean intersection over union(MIoU)were selected to evaluate the efficiency of image segmentation results.In comparison with the original MedSAM model,the ablation experiment systematically evaluated the influence of key components on the model performance.The sensitivities of MedSAM,the Segment Anything Model(SAM)for medical image segmentation(SAM-Med2D)and DP-MedSAM in the mandible,left optic nerve,and left parotid gland were compared.RESULTS AND CONCLUSION:(1)By verifying the impact of the number of point prompts on segmentation results on the HaN-Seg dataset,the experimental results indicated that the optimal Dice score was achieved with the addition of three points.(2)DP-MedSAM demonstrated performance improvements compared with MedSAM and SAM-Med2D on two datasets(HaN and Public Domain Database for Computational Anatomy).Especially on the Public Domain Database for Computational Anatomy dataset,in terms of the MIoU metric,DP-MedSAM outperformed MedSAM by 6.59％and SAM-Med2D by 37.35％;in terms of the Dice metric,DP-MedSAM outperformed MedSAM and SAM-Med2D by 4.34％and 25.32％,respectively.(3)The ablation experiment results showed that removing the texture feature extraction module in the DP-MedSAM model,relying solely on original image features,led to a significant decrease in results on the test set.Furthermore,removing the vector cache database and its retrieval enhancement function from the model,which deprived the ability of the model to perform similarity retrieval using an external knowledge base,further reduced model performance.(4)Under conditions of limited data resources,the DP-MedSAM model outperformed the other two models in all evaluation metrics.The DP-MedSAM model performed excellently when processing simple and moderately difficult samples,demonstrating a clear advantage over the other two models and indicating good generalization ability.Processing the fine structures of difficult samples placed higher demands on the model's segmentation capabilities.Although the performance of the DP-MedSAM model declined slightly,it still outperformed the other two models.(5)This study proposes an innovative craniocerebral tissue segmentation model,DP-MedSAM,which improves the baseline model's performance in capturing local details and global structural information in medical images by introducing target region texture feature extraction.Through vector similarity retrieval technology,DP-MedSAM can retrieve the feature vector most similar to the current target region from a pre-constructed vector database,providing more precise guiding information for the segmentation process.

Gastric cancer is a common malignant tumor of the digestive tract and can be classified as “fullness of the stomach”， “epigastric pain”， “noise” and other categories in the field of traditional Chinese medicine. Sijunzi decoction is composed of Panax ginseng， Poria cocos， Atractylodes macrocephala， and honey-fried Glycyrrhiza uralensis， and it has the effect of tonifying qi and strengthening the spleen. This article summarizes the active ingredients， mechanism of action， and clinical application research progress of Sijunzi decoction in treating gastric cancer. The results show that the main active ingredients of Sijunzi decoction include ginsenosides， atractylenolide， pachymic acid， glycyrrhizic acid， etc.； Sijunzi decoction and its effective ingredients can play an anti-gastric cancer role by inhibiting the proliferation of gastric cancer cell， inducing apoptosis of gastric cancer cell， enhancing gastric cancer cell chemotherapy sensitivity， and inhibiting invasion and metastasis of gastric cancer cell. In addition， Sijunzi decoction can enhance the efficacy of chemotherapy drugs， strengthen the immune function of the body and lower serum cancer marker levels during the clinical treatment of gastric cancer.

Objective To analyze the risk of bias during the experimental process and the shortcomings of the research report by evaluating the methodological and reporting quality of animal experimental studies on the prevention and treatment of precancerous lesions of gastric cancer(PLGC)using TCM compounds.To provide reference for improving the quality of animal experimental research on the prevention and treatment of PLGC with TCM compounds.Methods Experimental literature about the prevention and treatment of PLGC with TCM compounds was retrieved from CNKI,Wanfang Data,VIP,CBM,PubMed,Cochrane Library,Web of science and Embase from January 1,2014 to February 23,2024.SYRCLE assessment tool and ARRIVE 2.0 guideline were used to score the included literature and calculate the"low-risk"compliance rate for each item.Results Totally 213 articles were finally included,including 189 Chinese articles and 24 English articles.The SYRCLE tool score was(12.86±1.29)points,and the"low risk"compliance rate was 32.79％.The score of the necessary items of the ARRIVE 2.0 guideline was(24.15±2.80)points,and the"low risk"compliance rate was 49.08％;the score of the recommended items was(11.28±3.40)points,and the"low risk"compliance rate was 30.27％.In the SYRCLE tool evaluation,144(67.61％)studies did not elaborate on the method of generating the allocation sequence.All studies did not describe the adequacy of allocation concealment and the blinding method in the implementation of bias.Only 51 studies(23.94％)explicitly proposed the success criteria for PLGC modeling,only 66 studies(30.96％)provided detailed information on the statistical methods used,29 studies(13.62％)provided complete ethical statements,and 22 studies(10.33％)reported conflicts of interest.Conclusion There are many problems in the methodological quality and reporting quality of animal experimental literature on the prevention and treatment of PLGC with TCM compounds published from 2014 to 2024,especially the implementation of the random blinding strategy during the experimental process,the calculation details of the sample size,and the reporting of inclusion and exclusion criteria,etc.There are many deficiencies in this aspect.It is recommended to refer to the SYRCLE evaluation tool and the ARRIVE 2.0 guideline list to design and report the research plan,thereby improving the credibility and standardization of the PLGC animal experimental research results.

Objective:To analyze the epidemiological characteristics of severe fever with thrombocytopenia syndrome (SFTS) in Beijing in 2024, to investigate the infection status of reservoir hosts, vector organisms, and baseline human populations, and provide a scientific basis for formulating prevention and control strategies.Methods:Epidemiological surveys were conducted on all confirmed cases. Serum samples from healthy populations and reservoir hosts were collected for SFTSV antibody detection. Questing ticks were monitored using the flagging method. Real-time fluorescent quantitative PCR was employed to detect SFTSV in cases, reservoir hosts, and ticks. Positive samples underwent whole-genome sequencing and genetic evolution analysis.Results:In 2024, Beijing reported 15 locally infected cases with 4 deaths. The age of onset ranged from 50 to 80 years (median: 66 years). Cases showed a certain degree of geographical clustering, with June being the peak month of onset. The affected population was predominantly farmers, with a male-to-female ratio of 3∶2. Animal contact history emerged as a significant risk factor alongside tick bites. Parthenogenetic tick populations were identified in Pinggu district, while SFTSV-carrying ticks were detected in endemic areas (Mentougou, Shijingshan, and Fengtai Districts). Viral presence was also confirmed in ticks or dogs from non-endemic areas. Sequencing and phylogenetic analysis revealed stable clustering of strains into two distinct genotypes (A and B). Antibody-positive individuals were identified in healthy populations from non-endemic areas.Conclusions:The incidence of SFTS in Beijing is increasing, with natural viral circulation already established in non-endemic regions. Enhanced surveillance and adjusted prevention strategies are urgently needed.

Objective To explore the problems arising from the safety content in the instructions of Chinese patent medicines containing bitter almonds and to make suggestions.Methods By searching the Chinese patent medicines containing bitter almonds in the"National Basic Medical Insurance,Work Injury Insurance and Maternity Insurance Drug List(2022)"of the Medication Assistant and Yaozhi Online,the article collated their primary functions,composition,adverse reactions,contraindi-cations to medication,warnings,and precautions.The article entered the collected information into the Excel 2021 version,analyzed the summarized data,and made suggestions for the safety warning information in the instructions of Chinese patent medicines con-taining bitter almonds based on the results of the statistics.Results Among the 1 381 kinds of patent medicines listed in the"National Basic Medical Insurance,Work Injury Insurance,and Maternity Insurance Drug List(2022)",there are 67 varieties of Chinese patent medicines containing bitter almonds,and there were missing safety contents in the collected instructions.Among them,only five types were clearly labeled with specific contents of warnings,17 types were clearly labeled with adverse reactions,24 types were clearly labeled with contraindications,and 58 types were clearly labeled with precautions.However,in terms of the content of bitter almonds and prescription ratio,the maximum daily dosage of 2 out of 67 Chinese patent medicines containing bit-ter almonds exceeded the dosage of the Chinese Pharmacopoeia,and the prescription ratio of 14 Chinese patent medicines excee-ded 10％;in terms of the combination and dosing,25 out of 67 Chinese patent medicines containing bitter almond were dosed with other poisonous traditional Chinese medicines,and the above medicines have high safety risks.The information on their safety should be increased,and their safety information should be increased.Conclusions The safety-related warnings in the instruc-tions for Chinese patent medicines containing bitter almonds are not comprehensive enough.It is recommended to strengthen the management of the whole life cycle of drugs,increase the warnings of level 1 high-risk varieties,and improve adverse reactions,contraindications,and precautions according to the Technical Guiding Principles for Revision of Safety Information in Marketed Chinese Patent Medicine Instructions(Trial).

Objective To analyze the risk of bias during the experimental process and the shortcomings of the research report by evaluating the methodological and reporting quality of animal experimental studies on the prevention and treatment of precancerous lesions of gastric cancer(PLGC)using TCM compounds.To provide reference for improving the quality of animal experimental research on the prevention and treatment of PLGC with TCM compounds.Methods Experimental literature about the prevention and treatment of PLGC with TCM compounds was retrieved from CNKI,Wanfang Data,VIP,CBM,PubMed,Cochrane Library,Web of science and Embase from January 1,2014 to February 23,2024.SYRCLE assessment tool and ARRIVE 2.0 guideline were used to score the included literature and calculate the"low-risk"compliance rate for each item.Results Totally 213 articles were finally included,including 189 Chinese articles and 24 English articles.The SYRCLE tool score was(12.86±1.29)points,and the"low risk"compliance rate was 32.79％.The score of the necessary items of the ARRIVE 2.0 guideline was(24.15±2.80)points,and the"low risk"compliance rate was 49.08％;the score of the recommended items was(11.28±3.40)points,and the"low risk"compliance rate was 30.27％.In the SYRCLE tool evaluation,144(67.61％)studies did not elaborate on the method of generating the allocation sequence.All studies did not describe the adequacy of allocation concealment and the blinding method in the implementation of bias.Only 51 studies(23.94％)explicitly proposed the success criteria for PLGC modeling,only 66 studies(30.96％)provided detailed information on the statistical methods used,29 studies(13.62％)provided complete ethical statements,and 22 studies(10.33％)reported conflicts of interest.Conclusion There are many problems in the methodological quality and reporting quality of animal experimental literature on the prevention and treatment of PLGC with TCM compounds published from 2014 to 2024,especially the implementation of the random blinding strategy during the experimental process,the calculation details of the sample size,and the reporting of inclusion and exclusion criteria,etc.There are many deficiencies in this aspect.It is recommended to refer to the SYRCLE evaluation tool and the ARRIVE 2.0 guideline list to design and report the research plan,thereby improving the credibility and standardization of the PLGC animal experimental research results.

Objective:To analyze the epidemiological characteristics of severe fever with thrombocytopenia syndrome (SFTS) in Beijing in 2024, to investigate the infection status of reservoir hosts, vector organisms, and baseline human populations, and provide a scientific basis for formulating prevention and control strategies.Methods:Epidemiological surveys were conducted on all confirmed cases. Serum samples from healthy populations and reservoir hosts were collected for SFTSV antibody detection. Questing ticks were monitored using the flagging method. Real-time fluorescent quantitative PCR was employed to detect SFTSV in cases, reservoir hosts, and ticks. Positive samples underwent whole-genome sequencing and genetic evolution analysis.Results:In 2024, Beijing reported 15 locally infected cases with 4 deaths. The age of onset ranged from 50 to 80 years (median: 66 years). Cases showed a certain degree of geographical clustering, with June being the peak month of onset. The affected population was predominantly farmers, with a male-to-female ratio of 3∶2. Animal contact history emerged as a significant risk factor alongside tick bites. Parthenogenetic tick populations were identified in Pinggu district, while SFTSV-carrying ticks were detected in endemic areas (Mentougou, Shijingshan, and Fengtai Districts). Viral presence was also confirmed in ticks or dogs from non-endemic areas. Sequencing and phylogenetic analysis revealed stable clustering of strains into two distinct genotypes (A and B). Antibody-positive individuals were identified in healthy populations from non-endemic areas.Conclusions:The incidence of SFTS in Beijing is increasing, with natural viral circulation already established in non-endemic regions. Enhanced surveillance and adjusted prevention strategies are urgently needed.

Objective To explore the problems arising from the safety content in the instructions of Chinese patent medicines containing bitter almonds and to make suggestions.Methods By searching the Chinese patent medicines containing bitter almonds in the"National Basic Medical Insurance,Work Injury Insurance and Maternity Insurance Drug List(2022)"of the Medication Assistant and Yaozhi Online,the article collated their primary functions,composition,adverse reactions,contraindi-cations to medication,warnings,and precautions.The article entered the collected information into the Excel 2021 version,analyzed the summarized data,and made suggestions for the safety warning information in the instructions of Chinese patent medicines con-taining bitter almonds based on the results of the statistics.Results Among the 1 381 kinds of patent medicines listed in the"National Basic Medical Insurance,Work Injury Insurance,and Maternity Insurance Drug List(2022)",there are 67 varieties of Chinese patent medicines containing bitter almonds,and there were missing safety contents in the collected instructions.Among them,only five types were clearly labeled with specific contents of warnings,17 types were clearly labeled with adverse reactions,24 types were clearly labeled with contraindications,and 58 types were clearly labeled with precautions.However,in terms of the content of bitter almonds and prescription ratio,the maximum daily dosage of 2 out of 67 Chinese patent medicines containing bit-ter almonds exceeded the dosage of the Chinese Pharmacopoeia,and the prescription ratio of 14 Chinese patent medicines excee-ded 10％;in terms of the combination and dosing,25 out of 67 Chinese patent medicines containing bitter almond were dosed with other poisonous traditional Chinese medicines,and the above medicines have high safety risks.The information on their safety should be increased,and their safety information should be increased.Conclusions The safety-related warnings in the instruc-tions for Chinese patent medicines containing bitter almonds are not comprehensive enough.It is recommended to strengthen the management of the whole life cycle of drugs,increase the warnings of level 1 high-risk varieties,and improve adverse reactions,contraindications,and precautions according to the Technical Guiding Principles for Revision of Safety Information in Marketed Chinese Patent Medicine Instructions(Trial).

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires